In data mining, clustering can be used to group data objects based on similarities between the objects. Clustering can be useful because it can provide different perspectives on large sets of data. For example, in an enterprise setting, an enterprise may have a large corpus of documents. Clustering can be applied to the corpus to group the documents into multiple clusters. These clusters can reveal similarities between the clustered documents, enabling the enterprise to make more efficient use of its data and gain insights that may otherwise be difficult to draw.